LINCS L1000 dataset-based repositioning of CGP-60474 as a highly potent anti-endotoxemic agent.

ABSTRACT: Sepsis is one of the most common clinical syndromes that causes death and disability. Although many studies have developed drugs for sepsis treatment, none have decreased the mortality rate. The aim of this study was to identify a novel treatment option for sepsis using the library of integrated network-based cellular signatures (LINCS) L1000 perturbation dataset based on an in vitro and in vivo sepsis model. Sepsis-related microarray studies of early-stage inflammatory processes in patients and innate immune cells were collected from the Gene Expression Omnibus (GEO) data repository and used for candidate drug selection based on the LINCS L1000 perturbation dataset. The anti-inflammatory effects of the selected candidate drugs were analyzed using activated macrophage cell lines. CGP-60474

SUBMITTER: Han HW 

PROVIDER: S-EPMC6175892 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature